Different methods of 3D QRS area calculation from vectorcardiographic X, Y, and Z Leads.

3DQRSarea is a strong marker for cardiac resynchronization therapy and can be obtained by taking the (i) summation or the (ii) difference of the areas subtended by positive and negative deflections in X, Y, Z vectorcardiographic electrocardiogram (ECG) leads. We correlated both methods with the instantaneous-absolute-3D-voltage-time-integral (VTIQRS-3D). 3DQRSarea consistently underestimated the VTIQRS -3D, but the summation method was a closer and more reliable approximation. The dissimilarity was less apparent in left bundle branch block (r2 summation .996 vs. difference .972) and biventricular paced ECGs (r2 .996 vs. .957) but was more apparent in normal ECGs (r2 .988 vs. .653).

Electrocardiographic Z-axis QRS-T voltage-time-integral in patients with typical right bundle branch block - Correlation with echocardiographic right ventricular size and function.

BACKGROUND: Right bundle branch block (RBBB) can be benign or associated with right ventricular (RV) functional and structural abnormalities. Our aim was to evaluate QRS-T voltage-time-integral (VTI) compared to QRS duration and lead V1 R' as markers for RV abnormalities. METHODS: We included adults with an ECG demonstrating RBBB and echocardiogram obtained within 3 months of each other, between 2010 and 2020. VTIQRS and VTIQRST were obtained for 12 standard ECG leads, reconstructed vectorcardiographic X, Y, Z leads and root-mean-squared (3D) ECG. Age, sex and BSA-adjusted linear regressions were used to assess associations of QRS duration, amplitudes, VTIs and lead V1 R' duration/VTI with echocardiographic tricuspid annular plane systolic excursion (TAPSE), RV tissue Doppler imaging S', basal and mid diameter, and systolic pressure (RVSP). RESULTS: Among 782 patients (33% women, age 71 ± 14 years) with RBBB, R' duration in lead V1 was modestly associated with RV S', RV diameters and RVSP (all p ≤ 0.03). QRS duration was more strongly associated with RV diameters (both p < 0.0001). AmplitudeQRS-Z was modestly correlated with all 5 RV echocardiographic variables (all p ≤ 0.02). VTIR'-V1 was more strongly associated with TAPSE, RV S' and RVSP (all p ≤ 0.0003). VTIQRS-Z and VTIQRST-Z were among the strongest correlates of the 5 RV variables (all p < 0.0001). VTIQRST-Z.√BSA cutoff of ≥62 µVsm had sensitivity 62.7% and specificity 65.7% for predicting ≥3 of 5 abnormal RV variables (AUC 0.66; men 0.71, women 0.60). CONCLUSION: In patients with RBBB, VTIQRST-Z is a stronger predictor of RV dysfunction and adverse remodeling than QRS duration and lead V1 R'.

Evaluation of electrocardiographic criteria for predicting left ventricular hypertrophy and dilation in presence of left bundle branch block.

BACKGROUND: The utility of standard published electrocardiographic (ECG) criteria for left ventricular hypertrophy (LVH) in patients with left bundle branch block (LBBB) is not established. We have previously shown that in ECGs demonstrating LBBB, QRS duration outperforms vectorcardiographic X, Y, Z lead and root-mean-squared (3D) amplitudes and voltage-time-integrals in diagnosing LVH and dilation. We sought to evaluate diagnostic yields of published LVH criteria versus QRS duration for ECG based diagnosis of LVH and dilation in presence of LBBB. METHODS: We included adult patients with typical LBBB having ECG and transthoracic echocardiogram performed within 3 months of each other in 2010-2020. We obtained area under receiver-operator characteristic curve (AUC) for QRS duration and each of the published ECG LVH criteria to predict increased LV mass indexed (↑LVMi, women >95 g/m2, men >115 g/m2) and LV end diastolic volume indexed (↑LVEDVi, women >61 mL/m2, men >74 mL/m2). RESULTS: Among 413 adults (53 % women, age 73 ± 12 yr) with LBBB, the traditional LVH criteria performed poorly to detect ↑LVMi or ↑LVEDVi. Cornell voltage-duration product had the highest AUCs (↑LVMi 0.634, ↑LVEDVi 0.580). QRS duration had a higher AUC for diagnosing ↑LVMi (women 0.657, men 0.703) and ↑LVEDVi (women 0.668, men 0.699) compared to any other criteria. CONCLUSIONS: In patients with LBBB, prolonged QRS duration (women ≥150 ms, men ≥160 ms) is a superior predictor of LVH and dilation than traditional ECG-based LVH criteria.

Electrocardiographic prediction of left ventricular hypertrophy in women and men with left bundle branch block - Comparison of QRS duration, amplitude and voltage-time-integral.

BACKGROUND: Standard ECG criteria for left ventricular (LV) hypertrophy rely on QRS amplitudes. However, in the setting of left bundle branch block (LBBB), ECG correlates of LV hypertrophy are not well established. We sought to evaluate quantitative ECG predictors of LV hypertrophy in the presence of LBBB. METHODS: We included adult patients with typical LBBB having ECG and transthoracic echocardiogram performed within 3 months of each other in 2010-2020. Orthogonal X, Y, Z leads were reconstructed from digital 12­lead ECGs using Kors's matrix. In addition to QRS duration, we evaluated QRS amplitudes and voltage-time-integrals (VTIs) from all 12 leads, X, Y, Z leads and 3D (root-mean-squared) ECG. We used age, sex and BSA-adjusted linear regressions to predict echocardiographic LV calculations (mass, end-diastolic and end-systolic volumes, ejection fraction) from ECG, and separately generated ROC curves for predicting echocardiographic abnormalities. RESULTS: We included 413 patients (53% women, age 73 ± 12 years). All 4 echocardiographic LV calculations were most strongly correlated with QRS duration (all p < 0.00001). In women, QRS duration ≥ 150 ms had sensitivity/specificity 56.3%/64.4% for increased LV mass and 62.7%/67.8% for increased LV end-diastolic volume. In men, QRS duration ≥ 160 ms had a sensitivity/specificity 63.1%/72.1% for increased LV mass and 58.3%/74.5% for increased LV end-diastolic volume. QRS duration was best able to discriminate eccentric hypertrophy (area under ROC curve 0.701) and increased LV end-diastolic volume (0.681). CONCLUSIONS: In patients with LBBB, QRS duration (≥ 150 in women and ≥ 160 in men) is a superior predictor of LV remodeling esp. eccentric hypertrophy and dilation.

Machine learning to classify left ventricular hypertrophy using ECG feature extraction by variational autoencoder.

Background: Traditional ECG criteria for left ventricular hypertrophy (LVH) have low diagnostic yield. Machine learning (ML) can improve ECG classification. Methods: ECG summary features (rate, intervals, axis), R-wave, S-wave and overall-QRS amplitudes, and QRS/QRST voltage-time integrals (VTIs) were extracted from 12-lead, vectorcardiographic X-Y-Z-lead, and root-mean-square (3D) representative-beat ECGs. Latent features were extracted by variational autoencoder from X-Y-Z and 3D representative-beat ECGs. Logistic regression, random forest, light gradient boosted machine (LGBM), residual network (ResNet) and multilayer perceptron network (MLP) models using ECG features and sex, and a convolutional neural network (CNN) using ECG signals, were trained to predict LVH (left ventricular mass indexed in women >95 g/m², men >115 g/m²) on 225,333 adult ECG-echocardiogram (within 45 days) pairs. AUROCs for LVH classification were obtained in a separate test set for individual ECG variables, traditional criteria and ML models. Results: In the test set (n=25,263), AUROC for LVH classification was higher for ML models using ECG features (LGBM 0.790, MLP 0.789, ResNet 0.788) as compared to the best individual variable (VTI QRS-3D 0.677), the best traditional criterion (Cornell voltage-duration product 0.647) and CNN using ECG signal (0.767). Among patients without LVH who had a follow-up echocardiogram >1 (closest to 5) years later, LGBM false positives, compared to true negatives, had a 2.63 (95% CI 2.01, 3.45)-fold higher risk for developing LVH (p<0.0001). Conclusions: ML models are superior to traditional ECG criteria to classify-and predict future-LVH. Models trained on extracted ECG features, including variational autoencoder latent variables, outperformed CNN directly trained on ECG signal.